Using RNA Sequence and Structure for the Prediction of Riboswitch Aptamer: A Comprehensive Review of Available Software and Tools

Abstract

RNA molecules are essential players in many fundamental biological processes. Prokaryotes and eukaryotes have distinct RNA classes with specific structural features and functional roles. Computational prediction of protein structures is a research field in which high confidence three-dimensional protein models can be proposed based on the sequence alignment between target and templates. However, to date, only a few approaches have been developed for the computational prediction of RNA structures. Similar to proteins, RNA structures may be altered due to the interaction with various ligands, including proteins, other RNAs, and metabolites. A riboswitch is a molecular mechanism, found in the three kingdoms of life, in which the RNA structure is modified by the binding of a metabolite. It can regulate multiple gene expression mechanisms, such as transcription, translation initiation, and mRNA splicing and processing. Due to their nature, these entities also act on the regulation of gene expression and detection of small metabolites and have the potential to helping in the discovery of new classes of antimicrobial agents. In this review, we describe software and web servers currently available for riboswitch aptamer identification and secondary and tertiary structure prediction, including applications.

Challenges and approaches to predicting RNA with multiple functional structures

“…In each case, existing RNA structure prediction tools were adapted to solve the specific RNA folding problems. In addition to all the structures of riboswitches (Antunes et al 2018), these new NMR and smFRET approaches to characterization of RNA with more than one functional structure provide new test cases and insights into how an RNA sequence can encode and utilize many different shapes and functions. Further development of RNA structure prediction tools will be necessary to meet these challenges.…”

“…Similarly, the idea of one RNA sequence folding into a single lowest energy structure is fading as new RNA structures and functions are discovered. Riboswitches, a mechanism of gene regulation primarily known in prokaryotes that responds to metabolites with an RNA conformational switch, are the simplest case of an RNA sequence with two functional structures (Antunes et al 2018). A recent genome-wide study of RNA base-pairing reveals that approximately 20% of eukaryotic RNA fold into multiple shapes in vivo, as evidenced by crosslinking pairs that are incompatible with a single structure (Lu et al 2016).…”

“…This review focuses on current computational methods that address RNA folding challenges for predictions of RNA with multiple folds. Other recent reviews aptly provide an update on RNA folding tools (Fallmann et al 2017;Lim and Brown 2018) and approaches specific for RNA riboswitch aptamers (Antunes et al 2018). In this review, after a brief discussion of the RNA folding problem, we describe a combinatorially complete approach, two algorithms that analyze the Boltzmann ensemble to identify sequences with multiple folds, and three free energy minimization approaches to predicting RNA structures with more than one functional fold.…”

Pseudo aptamer expands aptamer’s applications

“…Once binding to the receptor, it will disable the function of the protein in the manner of proper conformed complex, or change the conformations of some proteins behaved molecular switches in some case. 11,12 As recently developed, an important benefit of aptamer technology is that fine ligand allows for rapid and parallel identification of any actually targeted molecules simultaneously and automatically. 13 Therefore, aptamer technology is well suited to address the growing needs for functional screen and validation of high-throughput bioactivities.…”

Riboflow: using deep learning to classify riboswitches with ~99% accuracy

“…Since the discovery of riboswitches [30,31], many computational efforts have been advanced for their characterisation, notably Infernal [32], Riboswitch finder [33], RibEx [34], RiboSW [35] and DRD [36], and reviewed in Clote [37] and Antunes et al [38]. These methods used probabilistic models of known classes with or without secondary structure information to infer or predict the riboswitch class.…”